Programming Constructs to Enable Formation of Efficient Algorithm Mapping for ExaScale Processors

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-12-C-0152
Agency Tracking Number: O11B-T02-1011
Amount: $99,998.00
Phase: Phase I
Program: STTR
Awards Year: 2012
Solicitation Year: 2011
Solicitation Topic Code: OSD11-T02
Solicitation Number: 2011.B
Small Business Information
Frontier Technology, Inc.
75 Aero Camino, Suite A, Goleta, CA, -
DUNS: 153927827
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Schmalz
 Principal Investigator (Univ of FL)
 (352) 505-1561
 mssz@cise.ufl.edu
Business Contact
 Rhonda Adawi
Title: Contracts Manager
Phone: (805) 685-6672
Email: radawi@fti-net.com
Research Institution
 University of Florida
 Cheryl L Coleman
 339 Weil Hall
Gainesville, FL, 32611-
 (352) 392-9447
 Nonprofit college or university
Abstract
Frontier Technology, Inc. (FTI) and its research partner University of Florida (UF) propose to develop new software tools for addressing the requirements of semi-automatically programming emerging classes of computational hardware for Exa-scale computing so as to benefit the DoD through reduced software production and overall life cycle costs with greater portability, fewer defects, and energy reduction. Phase I will: Co-design higher level algorithmic expressions with specific optimizations for parallelism and locality; Perform proof of concept measurements of improvements beyond what is achieved with common high level languages; Develop a mathematical basis of the underlying optimization model to illustrate the exploitation of parallelism and locality across stages of sensor signal processing; Benchmark model kernels relevant to Air Force sensor missions. Phase I will design, analyze, prototype, and demonstrate implementations of the above-listed computational strategies on a multicore CPU, graphics processing unit (GPU), or CPU-GPU cluster, with analysis of cluster size and proof of scalability. Phase II will implement new higher-level algorithm-specific language and optimizations; optimize these on mission relevant sensor data processing kernels; establish porting benefits; demonstrate parallelism, locality across stages of sensor computational chains, and methodology for application to Air Force missions and commercialization.

* information listed above is at the time of submission.

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